What is Instructional Resilience?

A short summary from our new publication in ETHE

Resilience is a psychological construct that refers to the ability to cope with challenging circumstances. Persons demonstrates resilience if they are able to positively adapt and develop during times that are considered psychologically averse, for example personal setbacks, social crises, and stress. Importantly, resilience is not merely a static trait but instead a dynamic process of adaptation that can encompass mental, physical, or even spiritual aspects. As such, resilience can change over time or even be the result of prior challenging episodes.

With the notion of instructional resilience we take this concept and apply it to teaching contexts. Similar to its broader counterpart, K-12 or university teacher demonstrate instructional resilience if they are able to adapt and maintain their standards of teaching during challenging circumstances. The sudden switch to emergency remote teaching (ERT) in the spring and summer of 2020, has presented many higher education teachers with such challenging teaching conditions. ERT has been unique in scope, as the majority of countries around the globe have made this sudden switch, and ERT has been unique in its effect, as many (or most) institutions were not sufficiently prepared for this switch, for example in terms of technical infrastructure and faculty competences.

Our recent study “Exploring Predictors of Instructional Resilience during Emergency Remote Teaching in Higher Education” (preprint here: OSF) adopts this resilience framing to highlight the challenges associated with the sudden shift to online-based teaching. We collected data from 102 higher education teachers during the winter of 2020/2021. Participants reported on, for example, their perceived teaching quality during ERT compared to their usual teaching, changes in workload, their usage of different online-based teaching strategies, their prior experience in online-teaching, their personality, as well as institutional factors like technical support.

Marco Kalz’s (2nd author) tweets about research questions and predictor variables that we looked at in our study.

What we found in our analysis:

Emergency remote teaching was indeed challenging for higher education teachers and their perceived teaching quality was reduced during these times. On average, teachers reported a ca. 25% drop of teaching quality and this was significantly associated with the perceived challenge during ERT. Higher education teachers reported increases in teaching load compared to before ERT but, interestingly, this was much lower than we had expected and the increase was barely significant. In fact, almost half our sample indicated a comparable teaching load.

Zero-order correlation between subjective teaching quality and perceived challenge during ERT.

Aside from these issues, ERT apparently also provided higher education teachers themselves with some learning experiences. They reported improved ability to teach with technology, compared to before ERT. In terms of learning design features that they found themselves to be able to implement well, they were most comfortable with presentation of content and delivery of feedback, whereas learning designs like group learning and discussions appeared less feasible.

Perceived (in-)ability with respect to learning design features, rated by HE teachers.

Regarding predictors for instructional resilience, we first noticed that age seemed to play a role; the age bracket of 36-56 years reported better results in maintaining teaching quality, compared to their younger colleagues. We found this to be a surprising result, as ERT had a major (educational-) technological component to it and we expected younger teachers to be better prepared for this. However, as we added more potential predictors, this association disappeared.

Looking at personality attributes, we found two salient personality predictors. Conscientiousness positively predicted instructional resilience, whereas impersonal causality orientation negatively predicted instructional resilience. To us, these results made sense and seem to be in line with how we would expect these attributes to be related with instructional resilience. These relationship remained even after including two more blocks of predictor variables.

In terms of relevant experience, we found that previous experience in teaching with technology was a significant positive predictor. Interestingly, participation in professional development, working in a TEL-related field or at a hybrid/distance education institution did not predict instructional resilience.

Finally, institutional factors like organizational, social, and technical support did not predict instructional resilience. Workload during ERT was also not associated with instructional resilience. Adding these factors to the model did not increase its predictive power, suggesting that these factors indeed hardly played a role.

Given these results, it appears that ERT indeed brought challenging circumstances for teaching, eliciting instructional resilience from higher education teachers. Certain personality configurations and prior experience played the most significant role in determining who succeeded in maintaining quality of teaching. Surprisingly, our results suggest that institutional factors played no role in instructional resilience. Thus, as a preliminary result, our investigation support the notion that differences in instructional resilience during ERT were largely determined by the individual resources of HE teachers.


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